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SAEHD:

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added option Eyes priority (y/n)

	fix eye problems during training  ( especially on HD architectures )
	by forcing the neural network to train eyes with higher priority
	before/after https://i.imgur.com/YQHOuSR.jpg

	It does not guarantee the right eye direction.
This commit is contained in:
Colombo 2020-02-18 14:30:07 +04:00
parent 4f928074b9
commit 9598ba0141
5 changed files with 105 additions and 60 deletions
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8
facelib/LandmarksProcessor.py
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@ -328,8 +328,8 @@ def expand_eyebrows(lmrks, eyebrows_expand_mod=1.0):
def get_image_hull_mask (image_shape, image_landmarks, eyebrows_expand_mod=1.0, ie_polys=None, color=(1,) ):
hull_mask = np.zeros(image_shape[0:2]+( len(color),),dtype=np.float32)
def get_image_hull_mask (image_shape, image_landmarks, eyebrows_expand_mod=1.0, ie_polys=None ):
hull_mask = np.zeros(image_shape[0:2]+(1,),dtype=np.float32)
lmrks = expand_eyebrows(image_landmarks, eyebrows_expand_mod)
@ -345,7 +345,7 @@ def get_image_hull_mask (image_shape, image_landmarks, eyebrows_expand_mod=1.0,
for item in parts:
merged = np.concatenate(item)
cv2.fillConvexPoly(hull_mask, cv2.convexHull(merged), color )
cv2.fillConvexPoly(hull_mask, cv2.convexHull(merged), (1,) )
if ie_polys is not None:
ie_polys.overlay_mask(hull_mask)
@ -390,7 +390,7 @@ def alpha_to_color (img_alpha, color):
def get_cmask (image_shape, lmrks, eyebrows_expand_mod=1.0):
h,w,c = image_shape
hull = get_image_hull_mask (image_shape, lmrks, eyebrows_expand_mod, color=(1,) )
hull = get_image_hull_mask (image_shape, lmrks, eyebrows_expand_mod )
result = np.zeros( (h,w,3), dtype=np.float32 )